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hitachi-speech / EEND

End-to-End Neural Diarization
MIT License
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The question about running lstm.sh #23

Open speaker-lover opened 3 years ago

speaker-lover commented 3 years ago

When i run the lstm.sh which in eend/egs/mini_librisppech/v1/local/run_blstm, i get the usingwarning: shared memory size is too small. Please set shared_mem option for MultiprocessIterator. Expect shared memory size: 4298700 bytes. Actual shared meory size: 3118900 bytes. But i use v100, 16G memory! The error information is follow.

Exception in main training loop: 'cupy.cuda.memory.MemoryPointer' object is not iterable Traceback (most recent call last): File "/home/chenyafeng.cyf/EEND-master/tools/miniconda3/envs/eend/lib/python3.7/site-packages/chainer/training/trainer.py", line 316, in run update() File "/home/chenyafeng.cyf/EEND-master/tools/miniconda3/envs/eend/lib/python3.7/site-packages/chainer/training/updaters/standard_updater.py", line 175, in update self.update_core() File "/home/chenyafeng.cyf/EEND-master/tools/miniconda3/envs/eend/lib/python3.7/site-packages/chainer/training/updaters/standard_updater.py", line 189, in update_core optimizer.update(loss_func, in_arrays) File "/home/chenyafeng.cyf/EEND-master/tools/miniconda3/envs/eend/lib/python3.7/site-packages/chainer/optimizer.py", line 825, in update loss = lossfun(*args, *kwds) File "/home/chenyafeng.cyf/EEND-master/eend/chainer_backend/models.py", line 588, in call F.stack([dc_loss(em, t) for (em, t) in zip(ems, ts)])) File "/home/chenyafeng.cyf/EEND-master/eend/chainer_backend/models.py", line 588, in F.stack([dc_loss(em, t) for (em, t) in zip(ems, ts)])) File "/home/chenyafeng.cyf/EEND-master/eend/chainer_backend/models.py", line 333, in dc_loss [int(''.join(str(x) for x in t), base=2) for t in label.data]] = 1 File "/home/chenyafeng.cyf/EEND-master/eend/chainer_backend/models.py", line 333, in dc_loss [int(''.join(str(x) for x in t), base=2) for t in label.data]] = 1 Will finalize trainer extensions and updater before reraising the exception. Traceback (most recent call last): File "../../../eend/bin/train.py", line 82, in train(args) File "/home/chenyafeng.cyf/EEND-master/eend/chainer_backend/train.py", line 223, in train trainer.run() File "/home/chenyafeng.cyf/EEND-master/tools/miniconda3/envs/eend/lib/python3.7/site-packages/chainer/training/trainer.py", line 349, in run six.reraise(exc_info) File "/home/chenyafeng.cyf/EEND-master/tools/miniconda3/envs/eend/lib/python3.7/site-packages/six.py", line 719, in reraise raise value File "/home/chenyafeng.cyf/EEND-master/tools/miniconda3/envs/eend/lib/python3.7/site-packages/chainer/training/trainer.py", line 316, in run update() File "/home/chenyafeng.cyf/EEND-master/tools/miniconda3/envs/eend/lib/python3.7/site-packages/chainer/training/updaters/standard_updater.py", line 175, in update self.update_core() File "/home/chenyafeng.cyf/EEND-master/tools/miniconda3/envs/eend/lib/python3.7/site-packages/chainer/training/updaters/standard_updater.py", line 189, in update_core optimizer.update(loss_func, in_arrays) File "/home/chenyafeng.cyf/EEND-master/tools/miniconda3/envs/eend/lib/python3.7/site-packages/chainer/optimizer.py", line 825, in update loss = lossfun(*args, **kwds) File "/home/chenyafeng.cyf/EEND-master/eend/chainer_backend/models.py", line 588, in call F.stack([dc_loss(em, t) for (em, t) in zip(ems, ts)])) File "/home/chenyafeng.cyf/EEND-master/eend/chainer_backend/models.py", line 588, in F.stack([dc_loss(em, t) for (em, t) in zip(ems, ts)])) File "/home/chenyafeng.cyf/EEND-master/eend/chainer_backend/models.py", line 333, in dc_loss [int(''.join(str(x) for x in t), base=2) for t in label.data]] = 1 TypeError: 'cupy.cuda.memory.MemoryPointer' object is not iterable

What should i do? I have no idea to solve it.

DiLiangWU commented 2 years ago

I have the same question when i run local/run_blstm.sh. Have you solved the problem yet?

TypeError: 'cupy.cuda.memory.MemoryPointer' object is not iterable

DiLiangWU commented 2 years ago

Maybe I have solved the error [TypeError: 'cupy.cuda.memory.MemoryPointer' object is not iterable]. You need change "for t in label.data" to "for t in label" in eend/chainer_backend/models.py, line 333.

But i still get the userwarning same with you. The warning information is: shared memory size is too small. Please set shared_mem option for MultiprocessIterator. Expect shared memory size: 2085180 bytes. Actual shared memory size: 1643796 bytes.